Opposite Prognostic Significance of Cellular and Serum Circulating MicroRNA-150 in Patients with Chronic Lymphocytic Leukemia.

MicroRNAs (or miRs) play a crucial role in chronic lymphocytic leukemia (CLL) physiopathology and prognosis. In addition, circulating microRNAs in body fluids have been proposed as new biomarkers. We investigated the expression of matched cellular and serum circulating microRNA-150 by quantitative real-time PCR (qPCR) from purified CD19(+) cells or from CLL serums obtained at diagnosis in a cohort of 273/252 CLL patients with a median follow-up of 78 months (range 7-380) and correlated it to other biological or clinical parameters. We showed that miR-150 was significantly overexpressed in CLL cells/serums compared with healthy subjects (P < 0.0001). Among CLL patients, a low cellular miR-150 expression level was associated with tumor burden, disease aggressiveness and poor prognostic factors. In contrast, a high level of serum miR-150 was associated with tumor burden markers and some markers of poor prognosis. Similarly, cellular and serum miR-150 also predicted treatment-free survival (TFS) and overall survival (OS) in an opposite manner: patients with low cellular/serum miR-150 levels have median TFS of 40/111 months compared with high-level patients who have a median TFS of 122/60 months (P < 0.0001/P = 0.0066). Similar results were observed for OS. We also found that cellular and serum miR-150 levels vary in an opposite manner during disease progression and that cellular miR-150 could be regulated by its release into the extracellular space. Cellular and serum levels of miR-150 are associated with opposite clinical prognoses and could be used to molecularly monitor disease evolution as a new prognostic factor in CLL.

Revisiting the sigmoidal curve fitting applied to quantitative real-time PCR data.

Amplification of a cDNA product by quantitative polymerase chain reaction (qPCR) gives rise to fluorescence sigmoidal curves from which absolute or relative target gene content of the sample is inferred. Besides comparative C(t) methods that require the construction of a reference standard curve, other methods that focus on the analysis of the sole amplification curve have been proposed more recently. Among them, the so-called sigmoidal curve fitting (SCF) method rests on the fitting of an empirical sigmoidal model to the experimental amplification data points, leading to the prediction of the amplification efficiency and to the calculation of the initial copy number in the sample. The implicit assumption of this method is that the sigmoidal model may describe an amplification curve quantitatively even in the portion of the curve where the fluorescence signal is hidden in the noise band. The theoretical basis of the SCF method was revisited here for defining the class of experimental amplification curves for which the method might be relevant. Applying the SCF method to six well-characterized different PCR assays illustrated possible pitfalls leading to biased estimates of the amplification efficiency and, thus, of the target gene content of a sample.